1. Field
The present disclosure relates to a sensor having an infrared sensing element and a method for using the sensor to determine colorants in prints.
2. Description of Related Art
In some image printing applications, it is necessary to convert sensor outputs (such as RGB, L*a*b* etc.) to actual area-coverage of the colorants (such as CMYK) in the hardcopy.
One example that requires such conversion is a system that is configured to monitor customer documents being printed in order to detect when calibration, maintenance or other service actions are necessary. For example, such a system is described in detail in U.S. Pat. No. 7,376,269 to R. Victor Klassen and Stephen C. Morgana titled “Method Of Comparing Electronic Images With Scans Of Prints To Detect Image Quality Defects,” which is hereby incorporated by reference in its entirety.
Another example that requires such conversion includes Automated Image Quality Diagnostics (AIQD). The AIQD system is invoked when the image printing system/copier senses a problem, when preventive maintenance is desired, or when the operator is not satisfied with machine performance.
In such conversions, the number of colorants (CMYK=4) is typically greater than the number of sensor outputs (RGB=3) available, and therefore the conversion from the sensor outputs to the actual area-coverage of the colorants in the hardcopy is not unique. Assumptions are often made in order to solve this conversion problem. Some methods (e.g., See U.S. Pat. No. 7,295,215 to R. Victor Klassen titled “Method For Calculating Colorant Error From Reflectance Error,” which is hereby incorporated by reference in its entirety) have been developed to solve this conversion problem and their accuracy relies heavily on the validity of the assumptions made.
One approach to solve this conversion problem is to assume a given Gray Component Replacement (GCR) strategy, which provides a relationship between the amount of K and the amount of CMY. This approach may be acceptable for some image printing applications such as color management with pre-specified GCR but does not work for print defect detection, since the defects are not constrained by the GCR strategy but are constrained by the state of the image printing system.
Another approach to solve this conversion problem is to use a more capable sensor (more than three-channel). For example, a spectrophotometer having 31-channels or more is used in color management. But the spectrophotometer has limited spatial resolution and is therefore not suitable for print defect detection. Yet another option for this conversion problem is to use a hyperspectral sensor or camera. However, a hyperspectral sensor or camera is very expensive and also has somewhat limited spatial and wavelength resolution. Moreover, even a system with high wavelength resolution, such as a spectrophotometer, is not well suited to this conversion problem, if the spectral data is limited to visible frequencies.
The present disclosure provides improvements over the prior art.